Spontaneous single-nucleotide substitutions and microsatellite mutations have distinct distributions of fitness effects.

The fitness effects of new mutations determine key properties of evolutionary processes. Beneficial mutations drive evolution, yet selection is also shaped by the frequency of small-effect deleterious mutations, whose combined effect can burden otherwise adaptive lineages and alter evolutionary trajectories and outcomes in clonally evolving organisms such as viruses, microbes, and tumors. The small effect sizes of these important mutations have made accurate measurements of their rates difficult. In microbes, assessing the effect of mutations on growth can be especially instructive, as this complex phenotype is closely linked to fitness in clonally evolving organisms. Here, we perform high-throughput time-lapse microscopy on cells from mutation-accumulation strains to precisely infer the distribution of mutational effects on growth rate in the budding yeast, Saccharomyces cerevisiae. We show that mutational effects on growth rate are overwhelmingly negative, highly skewed towards very small effect sizes, and frequent enough to suggest that deleterious hitchhikers may impose a significant burden on evolving lineages. By using lines that accumulated mutations in either wild-type or slippage repair-defective backgrounds, we further disentangle the effects of 2 common types of mutations, single-nucleotide substitutions and simple sequence repeat indels, and show that they have distinct effects on yeast growth rate. Although the average effect of a simple sequence repeat mutation is very small (approximately 0.3%), many do alter growth rate, implying that this class of frequent mutations has an important evolutionary impact.

The rate of spontaneous mutations in yeast deficient for MutSß function.

Mutations in simple sequence repeat loci underlie many inherited disorders in humans, and are increasingly recognized as important determinants of natural phenotypic variation. In eukaryotes, mutations in these sequences are primarily repaired by the MutSß mismatch repair complex. To better understand the role of this complex in mismatch repair and the determinants of simple sequence repeat mutation predisposition, we performed mutation accumulation in yeast strains with abrogated MutSß function. We demonstrate that mutations in simple sequence repeat loci in the absence of mismatch repair are primarily deletions. We also show that mutations accumulate at drastically different rates in short (<8 bp) and longer repeat loci. These data lend support to a model in which the mismatch repair complex is responsible for repair primarily in longer simple sequence repeats.

A standardized nomenclature and atlas of the female terminalia of Drosophila melanogaster.

The model organism Drosophila melanogaster has become a focal system for investigations of rapidly evolving genital morphology as well as the development and functions of insect reproductive structures. To follow up on a previous paper outlining unifying terminology for the structures of the male terminalia in this species, we offer here a detailed description of the female terminalia of D. melanogaster. Informative diagrams and micrographs are presented to provide a comprehensive overview of the external and internal reproductive structures of females. We propose a collection of terms and definitions to standardize the terminology associated with the female terminalia in D. melanogaster and we provide a correspondence table with the terms previously used. Unifying terminology for both males and females in this species will help to facilitate communication between various disciplines, as well as aid in synthesizing research across publications within a discipline that has historically focused principally on male features. Our efforts to refine and standardize the terminology should expand the utility of this important model system for addressing questions related to the development and evolution of animal genitalia, and morphology in general.

High-Throughput Live Imaging of Microcolonies to Measure Heterogeneity in Growth and Gene Expression.

Precise measurements of between- and within-strain heterogeneity in microbial growth rates are essential for understanding genetic and environmental inputs into stress tolerance, pathogenicity, and other key components of fitness. This manuscript describes a microscope-based assay that tracks approximately 105 Saccharomyces cerevisiae microcolonies per experiment. After automated time-lapse imaging of yeast immobilized in a multiwell plate, microcolony growth rates are easily analyzed with custom image-analysis software. For each microcolony, expression and localization of fluorescent proteins and survival of acute stress can also be monitored. This assay allows precise estimation of strains' average growth rates, as well as comprehensive measurement of heterogeneity in growth, gene expression, and stress tolerance within clonal populations.

Extent and context dependence of pleiotropy revealed by high-throughput single-cell phenotyping.

Pleiotropy-when a single mutation affects multiple traits-is a controversial topic with far-reaching implications. Pleiotropy plays a central role in debates about how complex traits evolve and whether biological systems are modular or are organized such that every gene has the potential to affect many traits. Pleiotropy is also critical to initiatives in evolutionary medicine that seek to trap infectious microbes or tumors by selecting for mutations that encourage growth in some conditions at the expense of others. Research in these fields, and others, would benefit from understanding the extent to which pleiotropy reflects inherent relationships among phenotypes that correlate no matter the perturbation (vertical pleiotropy). Alternatively, pleiotropy may result from genetic changes that impose correlations between otherwise independent traits (horizontal pleiotropy). We distinguish these possibilities by using clonal populations of yeast cells to quantify the inherent relationships between single-cell morphological features. Then, we demonstrate how often these relationships underlie vertical pleiotropy and how often these relationships are modified by genetic variants (quantitative trait loci [QTL]) acting via horizontal pleiotropy. Our comprehensive screen measures thousands of pairwise trait correlations across hundreds of thousands of yeast cells and reveals ample evidence of both vertical and horizontal pleiotropy. Additionally, we observe that the correlations between traits can change with the environment, genetic background, and cell-cycle position. These changing dependencies suggest a nuanced view of pleiotropy: biological systems demonstrate limited pleiotropy in any given context, but across contexts (e.g., across diverse environments and genetic backgrounds) each genetic change has the potential to influence a larger number of traits. Our method suggests that exploiting pleiotropy for applications in evolutionary medicine would benefit from focusing on traits with correlations that are less dependent on context.

A standardized nomenclature and atlas of the male terminalia of Drosophila melanogaster.

Animal terminalia represent some of the most diverse and rapidly evolving structures in the animal kingdom, and for this reason have been a mainstay in the taxonomic description of species. The terminalia of Drosophila melanogaster, with its wide range of experimental tools, have recently become the focus of increased interest in the fields of development, evolution, and behavior. However, studies from different disciplines have often used discrepant terminologies for the same anatomical structures. Consequently, the terminology of genital parts has become a barrier to integrating results from different fields, rendering it difficult to determine what parts are being referenced. We formed a consortium of researchers studying the genitalia of D. melanogaster to help establish a set of naming conventions. Here, we present a detailed visual anatomy of male genital parts, including a list of synonymous terms, and suggest practices to avoid confusion when referring to anatomical parts in future studies. The goal of this effort is to facilitate interdisciplinary communication and help newcomers orient themselves within the exciting field of Drosophila genitalia.

Feed-forward regulation adaptively evolves via dynamics rather than topology when there is intrinsic noise.

In transcriptional regulatory networks (TRNs), a canonical 3-node feed-forward loop (FFL) is hypothesized to evolve to filter out short spurious signals. We test this adaptive hypothesis against a novel null evolutionary model. Our mutational model captures the intrinsically high prevalence of weak affinity transcription factor binding sites. We also capture stochasticity and delays in gene expression that distort external signals and intrinsically generate noise. Functional FFLs evolve readily under selection for the hypothesized function but not in negative controls. Interestingly, a 4-node "diamond" motif also emerges as a short spurious signal filter. The diamond uses expression dynamics rather than path length to provide fast and slow pathways. When there is no idealized external spurious signal to filter out, but only internally generated noise, only the diamond and not the FFL evolves. While our results support the adaptive hypothesis, we also show that non-adaptive factors, including the intrinsic expression dynamics, matter.

Author Correction: Testing the key assumption of heritability estimates based on genome-wide genetic relatedness.

In the original paper, we used the variable "URBRUR08," from the 2008 survey wave as a measure of childhood urbanicity. Upon further investigation we realized that this variable actually measured Beale urban-rural code during the respondent's adulthood.  Thus, we reran our analysis of the pseudo-heritability of childhood urbanicity using the variable. The original results hold such that even with the first 20 principal components held constant, childhood urban-rural status appears to be ~20% "heritable" in GREML models-a figure that is actually higher than the original estimate reported in the paper (14% controlling for 25 PCs, 15% controlling for 10 PCs, and 29% controlling for two PCs). Meanwhile, the heritabilities of the other phenotypes-height, BMI and education-still do not change when they are residualized on childhood urbanicity. In other words, the original results of the paper do not change.

Decanalizing thinking on genetic canalization.

The concept of genetic canalization has had an abiding influence on views of complex-trait evolution. A genetically canalized system has evolved to become less sensitive to the effects of mutation. When a gene product that supports canalization is compromised, the phenotypic impacts of a mutation should be more pronounced. This expected increase in mutational effects not only has important consequences for evolution, but has also motivated strategies to treat disease. However, recent studies demonstrate that, when putative agents of genetic canalization are impaired, systems do not behave as expected. Here, we review the evidence that is used to infer whether particular gene products are agents of genetic canalization. Then we explain how such inferences often succumb to a converse error. We go on to show that several candidate agents of genetic canalization increase the phenotypic impacts of some mutations while decreasing the phenotypic impacts of others. These observations suggest that whether a gene product acts as a 'buffer' (lessening mutational effects) or a 'potentiator' (increasing mutational effects) is not a fixed property of the gene product but instead differs for the different mutations with which it interacts. To investigate features of genetic interactions that might predispose them toward buffering versus potentiation, we explore simulated gene-regulatory networks. Similarly to putative agents of genetic canalization, the gene products in simulated networks also modify the phenotypic effects of mutations in other genes without a strong overall tendency towards lessening or increasing these effects. In sum, these observations call into question whether complex traits have evolved to become less sensitive (i.e., are canalized) to genetic change, and the degree to which trends exist that predict how one genetic change might alter another's impact. We conclude by discussing approaches to address these and other open questions that are brought into focus by re-thinking genetic canalization.

Control of nongenetic heterogeneity in growth rate and stress tolerance of Saccharomyces cerevisiae by cyclic AMP-regulated transcription factors.

Genetically identical cells exhibit extensive phenotypic variation even under constant and benign conditions. This so-called nongenetic heterogeneity has important clinical implications: within tumors and microbial infections, cells show nongenetic heterogeneity in growth rate and in susceptibility to drugs or stress. The budding yeast, Saccharomyces cerevisiae, shows a similar form of nongenetic heterogeneity in which growth rate correlates positively with susceptibility to acute heat stress at the single-cell level. Using genetic and chemical perturbations, combined with high-throughput single-cell assays of yeast growth and gene expression, we show here that heterogeneity in intracellular cyclic AMP (cAMP) levels acting through the conserved Ras/cAMP/protein kinase A (PKA) pathway and its target transcription factors, Msn2 and Msn4, underlies this nongenetic heterogeneity. Lower levels of cAMP correspond to slower growth, as shown by direct comparison of cAMP concentration in subpopulations enriched for slower vs. faster growing cells. Concordantly, an endogenous reporter of this pathway's activity correlates with growth in individual cells. The paralogs Msn2 and Msn4 differ in their roles in nongenetic heterogeneity in a way that demonstrates slow growth and stress tolerance are not inevitably linked. Heterogeneity in growth rate requires each, whereas only Msn2 is required for heterogeneity in expression of Tsl1, a subunit of trehalose synthase that contributes to acute-stress tolerance. Perturbing nongenetic heterogeneity by mutating genes in this pathway, or by culturing wild-type cells with the cell-permeable cAMP analog 8-bromo-cAMP or the PKA inhibitor H89, significantly impacts survival of acute heat stress. Perturbations that increase intracellular cAMP levels reduce the slower-growing subpopulation and increase susceptibility to acute heat stress, whereas PKA inhibition slows growth and decreases susceptibility to acute heat stress. Loss of Msn2 reduces, but does not completely eliminate, the correlation in individual cells between growth rate and acute-stress survival, suggesting a major role for the Msn2 pathway in nongenetic heterogeneity but also a residual benefit of slow growth. Our results shed light on the genetic control of nongenetic heterogeneity and suggest a possible means of defeating bet-hedging pathogens or tumor cells by making them more uniformly susceptible to treatment.

Correction: A sibling method for identifying vQTLs.

[This corrects the article DOI: 10.1371/journal.pone.0194541.].

A sibling method for identifying vQTLs.

The propensity of a trait to vary within a population may have evolutionary, ecological, or clinical significance. In the present study we deploy sibling models to offer a novel and unbiased way to ascertain loci associated with the extent to which phenotypes vary (variance-controlling quantitative trait loci, or vQTLs). Previous methods for vQTL-mapping either exclude genetically related individuals or treat genetic relatedness among individuals as a complicating factor addressed by adjusting estimates for non-independence in phenotypes. The present method uses genetic relatedness as a tool to obtain unbiased estimates of variance effects rather than as a nuisance. The family-based approach, which utilizes random variation between siblings in minor allele counts at a locus, also allows controls for parental genotype, mean effects, and non-linear (dominance) effects that may spuriously appear to generate variation. Simulations show that the approach performs equally well as two existing methods (squared Z-score and DGLM) in controlling type I error rates when there is no unobserved confounding, and performs significantly better than these methods in the presence of small degrees of confounding. Using height and BMI as empirical applications, we investigate SNPs that alter within-family variation in height and BMI, as well as pathways that appear to be enriched. One significant SNP for BMI variability, in the MAST4 gene, replicated. Pathway analysis revealed one gene set, encoding members of several signaling pathways related to gap junction function, which appears significantly enriched for associations with within-family height variation in both datasets (while not enriched in analysis of mean levels). We recommend approximating laboratory random assignment of genotype using family data and more careful attention to the possible conflation of mean and variance effects.

Deep sequencing of natural and experimental populations of Drosophila melanogaster reveals biases in the spectrum of new mutations.

Mutations provide the raw material of evolution, and thus our ability to study evolution depends fundamentally on having precise measurements of mutational rates and patterns. We generate a data set for this purpose using (1) de novo mutations from mutation accumulation experiments and (2) extremely rare polymorphisms from natural populations. The first, mutation accumulation (MA) lines are the product of maintaining flies in tiny populations for many generations, therefore rendering natural selection ineffective and allowing new mutations to accrue in the genome. The second, rare genetic variation from natural populations allows the study of mutation because extremely rare polymorphisms are relatively unaffected by the filter of natural selection. We use both methods in Drosophila melanogaster, first generating our own novel data set of sequenced MA lines and performing a meta-analysis of all published MA mutations (∼2000 events) and then identifying a high quality set of ∼70,000 extremely rare (≤0.1%) polymorphisms that are fully validated with resequencing. We use these data sets to precisely measure mutational rates and patterns. Highlights of our results include: a high rate of multinucleotide mutation events at both short (∼5 bp) and long (∼1 kb) genomic distances, showing that mutation drives GC content lower in already GC-poor regions, and using our precise context-dependent mutation rates to predict long-term evolutionary patterns at synonymous sites. We also show that de novo mutations from independent MA experiments display similar patterns of single nucleotide mutation and well match the patterns of mutation found in natural populations.

Resolving the Complex Genetic Basis of Phenotypic Variation and Variability of Cellular Growth.

In all organisms, the majority of traits vary continuously between individuals. Explaining the genetic basis of quantitative trait variation requires comprehensively accounting for genetic and nongenetic factors as well as their interactions. The growth of microbial cells can be characterized by a lag duration, an exponential growth phase, and a stationary phase. Parameters that characterize these growth phases can vary among genotypes (phenotypic variation), environmental conditions (phenotypic plasticity), and among isogenic cells in a given environment (phenotypic variability). We used a high-throughput microscopy assay to map genetic loci determining variation in lag duration and exponential growth rate in growth rate-limiting and nonlimiting glucose concentrations, using segregants from a cross of two natural isolates of the budding yeast, Saccharomyces cerevisiae We find that some quantitative trait loci (QTL) are common between traits and environments whereas some are unique, exhibiting gene-by-environment interactions. Furthermore, whereas variation in the central tendency of growth rate or lag duration is explained by many additive loci, differences in phenotypic variability are primarily the result of genetic interactions. We used bulk segregant mapping to increase QTL resolution by performing whole-genome sequencing of complex mixtures of an advanced intercross mapping population grown in selective conditions using glucose-limited chemostats. We find that sequence variation in the high-affinity glucose transporter HXT7 contributes to variation in growth rate and lag duration. Allele replacements of the entire locus, as well as of a single polymorphic amino acid, reveal that the effect of variation in HXT7 depends on genetic, and allelic, background. Amplifications of HXT7 are frequently selected in experimental evolution in glucose-limited environments, but we find that HXT7 amplifications result in antagonistic pleiotropy that is absent in naturally occurring variants of HXT7 Our study highlights the complex nature of the genotype-to-phenotype map within and between environments.

Selection Transforms the Landscape of Genetic Variation Interacting with Hsp90.

The protein-folding chaperone Hsp90 has been proposed to buffer the phenotypic effects of mutations. The potential for Hsp90 and other putative buffers to increase robustness to mutation has had major impact on disease models, quantitative genetics, and evolutionary theory. But Hsp90 sometimes contradicts expectations for a buffer by potentiating rapid phenotypic changes that would otherwise not occur. Here, we quantify Hsp90's ability to buffer or potentiate (i.e., diminish or enhance) the effects of genetic variation on single-cell morphological features in budding yeast. We corroborate reports that Hsp90 tends to buffer the effects of standing genetic variation in natural populations. However, we demonstrate that Hsp90 tends to have the opposite effect on genetic variation that has experienced reduced selection pressure. Specifically, Hsp90 tends to enhance, rather than diminish, the effects of spontaneous mutations and recombinations. This result implies that Hsp90 does not make phenotypes more robust to the effects of genetic perturbation. Instead, natural selection preferentially allows buffered alleles to persist and thereby creates the false impression that Hsp90 confers greater robustness.

Sibling genes as environment: Sibling dopamine genotypes and adolescent health support frequency dependent selection.

While research consistently suggests siblings matter for individual outcomes, it remains unclear why. At the same time, studies of genetic effects on health typically correlate variants of a gene with the average level of behavioral or health measures, ignoring more complicated genetic dynamics. Using National Longitudinal Study of Adolescent Health data, we investigate whether sibling genes moderate individual genetic expression. We compare twin variation in health-related absences and self-rated health by genetic differences at three locations related to dopamine regulation and transport to test sibship-level cross-person gene-gene interactions. Results suggest effects of variation at these genetic locations are moderated by sibling genes. Although the mechanism remains unclear, this evidence is consistent with frequency dependent selection and suggests much genetic research may violate the stable unit treatment value assumption.

A Philosophical Perspective on Evolutionary Systems Biology.

Evolutionary systems biology (ESB) is an emerging hybrid approach that integrates methods, models, and data from evolutionary and systems biology. Drawing on themes that arose at a cross-disciplinary meeting on ESB in 2013, we discuss in detail some of the explanatory friction that arises in the interaction between evolutionary and systems biology. These tensions appear because of different modeling approaches, diverse explanatory aims and strategies, and divergent views about the scope of the evolutionary synthesis. We locate these discussions in the context of long-running philosophical deliberations on explanation, modeling, and theoretical synthesis. We show how many of the issues central to ESB's progress can be understood as general philosophical problems. The benefits of addressing these philosophical issues feed back into philosophy too, because ESB provides excellent examples of scientific practice for the development of philosophy of science and philosophy of biology.

Engineering and Biology: Counsel for a Continued Relationship.

Biologists frequently draw on ideas and terminology from engineering. Evolutionary systems biology-with its circuits, switches, and signal processing-is no exception. In parallel with the frequent links drawn between biology and engineering, there is ongoing criticism against this cross-fertilization, using the argument that over-simplistic metaphors from engineering are likely to mislead us as engineering is fundamentally different from biology. In this article, we clarify and reconfigure the link between biology and engineering, presenting it in a more favorable light. We do so by, first, arguing that critics operate with a narrow and incorrect notion of how engineering actually works, and of what the reliance on ideas from engineering entails. Second, we diagnose and diffuse one significant source of concern about appeals to engineering, namely that they are inherently and problematically metaphorical. We suggest that there is plenty of fertile ground left for a continued, healthy relationship between engineering and biology.

Shifting sugars and shifting paradigms.

No organism lives in a constant environment. Based on classical studies in molecular biology, many have viewed microbes as following strict rules for shifting their metabolic activities when prevailing conditions change. For example, students learn that the bacterium Escherichia coli makes proteins for digesting lactose only when lactose is available and glucose, a better sugar, is not. However, recent studies, including three PLOS Biology papers examining sugar utilization in the budding yeast Saccharomyces cerevisiae, show that considerable heterogeneity in response to complex environments exists within and between populations. These results join similar recent results in other organisms that suggest that microbial populations anticipate predictable environmental changes and hedge their bets against unpredictable ones. The classical view therefore represents but one special case in a range of evolutionary adaptations to environmental changes that all organisms face.